The inertial navigation system (INS) is a widely used technology for guidance and navigation of a vehicle. The INS is composed of an inertial measurement unit (IMU) and a processor wherein an IMU houses accelerometers and gyroscopes which are inertial sensors detecting platform motion with respect to an inertial coordinate system. A conventional computational scheme for an INS commonly known in the art offers an exact formula applicable well to a system with high-end inertial sensors such as ring laser gyros to track the platform six degrees of freedom without any conditions in the platform dynamics. An important advantage of the INS is independence from external support, i.e., it is self-contained. The INS, however, cannot provide high accuracy for a long range because errors accumulate over time, i.e., the longer travel time, the greater inaccuracy.
More recent development in the global positioning system (GPS) has made high accuracy vehicle navigation possible at low cost. The GPS provides accurate position and velocity over a longer time period, however, the GPS involves occasional large multipath errors and signal dropouts. This is because the GPS relies on GPS satellite signals which are susceptible to environmental conditions such as jamming, RF (radio frequency) interference, and multipath problems. Therefore, efforts are made to develop integrated INS/GPS navigation systems by combining the outputs of a GPS receiver and an INS using a Kalman filter to remedy the performance problems of both systems.
Inertial sensors used to be expensive and bulky, thus only used in precision application, e.g., aerospace and military navigation. For establishing an IMU package in a compact and inexpensive manner, efforts have been made to develop micro-electro mechanical system (MEMS) sensors resulting in commercialization of low-cost, small, but noisier MEMS inertial sensors. MEMS-INS application has interested the automotive industry as potential replacement for speed (or, odometry) pulses which give specific numbers of pulses per wheel rotation at the expense of tedious wiring. In MEMS-INS application, however, erroneous accelerations quickly accumulate when GPS dropouts because of the large amount of noise, bias, and limited accuracy in orientation determination.
This often results in erroneously estimated motion with increasing speed while actually being stationary. To prevent this issue and to take corrective action, Japanese Patent No. 3404905 issued to Matsushita discloses a technique to detect the stationary status by the amplitude of the acceleration vertical to the vehicle. This allows coarse detection of motion/stationary status of the vehicle by noisy vertical motion mainly due to the uneven road surface. The vertical acceleration, however, does not sense a vehicle's primary forward or backward motion resulting in often undetected vehicle motion. This issue becomes more and more serious as vehicle motion become quieter due to recent automotive technology development.
Meanwhile, U.S. Pre-Grant Publication number 2008-0071476 filed by Hoshizaki discloses a sophisticated technology to detect vehicle's stationary status using three-axis accelerometer and three-axis gyroscope outputs along a logical flowchart. Use of multiple gyroscopes is, however, hesitated in low-cost application such as automotive navigation because of their high cost compared to accelerometers: one single-axis MEMS gyroscope for automotive specification costs significantly more than one package of three-axis MEMS accelerometer unit for automotive specification.
Therefore, there is a need of a new architecture to detect the platform stationary status (1) very accurately applicable to today's high-performance (very quiet) automobiles; (2) with low-cost MEMS sensors, preferably without using gyroscopes; (3) preferably with free attachment angle and versatile platform applications.